Misestimation of Growing Season Length Due to Inaccurate Construction of Satellite Vegetation Index Time Series

被引:12
作者
Wang, Cong [1 ,2 ]
Zhu, Kai [1 ]
机构
[1] Univ Calif Santa Cruz, Dept Environm Studies, Santa Cruz, CA 95064 USA
[2] Univ Illinois, Champaign, IL USA
关键词
End of the growing season (EOS); land long-term data record normalized difference vegetation index (LTDR NDVI); land surface phenology (LSP); maximum value composite (MVC); start of the growing season (SOS); SPRING PHENOLOGY; CLIMATE; PRODUCTS; DATES;
D O I
10.1109/LGRS.2019.2895805
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Satellite-based vegetation index (VI) is widely used in monitoring land surface phenology (LSP). Currently, well-developed VI products utilize the maximum value composite (MVC) algorithm to produce a composite VI time series (TS). Many of these products, however, lack the actual acquisition elate (AD) of the VI value. As an alternative, the median or mean date of a composite period is used to reconstruct the VI TS, which might lead to bias on LSP detection. This letter quantifies the LSP bias in the Northern Hemisphere by generating a 15-day composited normalized difference vegetation index (NDVI) TS from the land long-term data record daily NDVI products using the MVC method. The results show that the AD of the NDVI value is usually later than the mean date of a composite period in spring and earlier in fall, effectively leading to a total overestimation of the growing season length of 5.91 days on average across the Northern Hemisphere (north of 30 degrees N). This bias has a significant spatial pattern with high values observed in Northeastern China, Central North America, and high-latitude areas. However, the temporal trend is not largely influenced overall. Accordingly, we suggest the research community using accurate temporal information, whenever possible, in extracting LSP from VI TS.
引用
收藏
页码:1185 / 1189
页数:5
相关论文
共 27 条
  • [1] Phenological Metrics Derived over the European Continent from NDVI3g Data and MODIS Time Series
    Atzberger, Clement
    Klisch, Anja
    Mattiuzzi, Matteo
    Vuolo, Francesco
    [J]. REMOTE SENSING, 2014, 6 (01) : 257 - 284
  • [2] Bachoo A, 2007, 2007 INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTI-TEMPORAL REMOTE SENSING IMAGES, P72
  • [3] Responses of spring phenology to climate change
    Badeck, FW
    Bondeau, A
    Böttcher, K
    Doktor, D
    Lucht, W
    Schaber, J
    Sitch, S
    [J]. NEW PHYTOLOGIST, 2004, 162 (02) : 295 - 309
  • [4] Three decades of multi-dimensional change in global leaf phenology
    Buitenwerf, Robert
    Rose, Laura
    Higgins, Steven I.
    [J]. NATURE CLIMATE CHANGE, 2015, 5 (04) : 364 - 368
  • [5] An improved logistic method for detecting spring vegetation phenology in grasslands from MODIS EVI time-series data
    Cao, Ruyin
    Chen, Jin
    Shen, Miaogen
    Tang, Yanhong
    [J]. AGRICULTURAL AND FOREST METEOROLOGY, 2015, 200 : 9 - 20
  • [6] A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter
    Chen, J
    Jönsson, P
    Tamura, M
    Gu, ZH
    Matsushita, B
    Eklundh, L
    [J]. REMOTE SENSING OF ENVIRONMENT, 2004, 91 (3-4) : 332 - 344
  • [7] Changes in satellite-derived spring vegetation green-up date and its linkage to climate in China from 1982 to 2010: a multimethod analysis
    Cong, Nan
    Wang, Tao
    Nan, Huijuan
    Ma, Yuecun
    Wang, Xuhui
    Myneni, Ranga B.
    Piao, Shilong
    [J]. GLOBAL CHANGE BIOLOGY, 2013, 19 (03) : 881 - 891
  • [8] Rapid changes in flowering time in British plants
    Fitter, AH
    Fitter, RSR
    [J]. SCIENCE, 2002, 296 (5573) : 1689 - 1691
  • [9] Comparison and Evaluation of Annual NDVI Time Series in China Derived from the NOAA AVHRR LTDR and Terra MODIS MOD13C1 Products
    Guo, Xiaoyi
    Zhang, Hongyan
    Wu, Zhengfang
    Zhao, Jianjun
    Zhang, Zhengxiang
    [J]. SENSORS, 2017, 17 (06):
  • [10] Quality assessment and improvement of temporally composited products of remotely sensed imagery by combination of VEGETATION 1 and 2 images
    Hagolle, O
    Lobo, A
    Maisongrande, P
    Cabot, F
    Duchemin, B
    De Pereyra, A
    [J]. REMOTE SENSING OF ENVIRONMENT, 2005, 94 (02) : 172 - 186